Adapted from the chapter Inuits and Illusions in the Time of the Most Polar Bears

The Inuit claim “it is the time of the most polar
bears.” By synthesizing their community’s observations they have demonstrated a
greater accuracy counting Bowhead whales and polar bears than the models of
credentialed scientists. To estimate correctly, it takes a village. In contrast
the “mark and recapture” study, which claimed the polar bears along South Beaufort Sea were victims of
catastrophic global warming and threatened with extinction, relied on the
subjective decisions of a handful of modelers.

In mark and recapture studies, the estimate of
population abundance is skewed by the estimate of survival. For example,
acknowledging the great uncertainty in his calculations of survival, in his
earlier studies polar beat expert Steven
Amstrup reported three different population estimates for bears along the South
Beaufort Sea. If he assumed the adult bears had an 82% chance of surviving into
the next year, the models calculated there were 1301 bears. If survivorship was
88%, the abundance climbed to 1776 bears. If he estimated survivorship at a
more robust 94%, then polar bear abundance climbed to 2490.1 Thus
depending on estimated survival rates, a mark-and-recapture study may conclude that the
population has doubled, or that it has suddenly crashed.

Here are the simplified basics of estimating
survival for any animal (brown bears in the cartoon, but this applies to polar bears too). In the cartoon assume the fenced-off area is your
study area. For statistical reasons you ignore observations outside that
designated area. During the first year, you reach into your study area and
capture four bears , which you then mark by
painting a big white cross on their chests. (Researchers first painted big
numbers on polar bears for easy identification from a helicopter, but the tourism
industry complained that it ruined photographs. They now use discreet ear tags
and a tattoo under their upper lip in case the tag falls off.)

The next year you return to your study area and
randomly capture four more bears. However, only two are marked with a white
cross. Now the researcher must decide what happened to the two missing bears
that were marked last year. Did they die or did they avoid detection? Assuming
they avoided detection, then survival is estimated to be 100%. Since the two recaptured
bears represent half of last year’s
marked bears, the models assume the four bears captured during the study’s
second year similarly represent about half
of the total population. So the models estimate that there were at least
eight bears within the study area.

However
the calculations change if the researcher assumes the missing marked bears
died. In this case, it means that in the second year you captured every possible marked bear. So your
model assumes that you also captured every possible bear in the study area. Now
the model estimates that there were only about four bears living in your study
area. Because the survival rates are greatly affected by this guesswork, these
estimates are called “apparent survival
rates.”

Apparent survival rates are heavily biased by any migration in and out of the
study area. The earliest mark and recapture models were tested on rodent
populations, and the statisticians warned that barriers should be erected to
prevent the rodents from moving. Otherwise all statistical calculations were
totally unreliable. But that tactic is impossible for highly migratory polar
bears.

Unlike other species that defend a territory with
reliable resources, polar bears never
defend territories. They walk and swim across great distances and will
congregate wherever the Arctic’s ever-shifting food supply becomes most
abundant. A study of radio-collared female bears
denning on Wrangel Island determined that after the bears left
the island they traveled an average distance of about 3700 miles.2
Although much of their travel is confined within a less extensive region, one
radio-collared female was observed in Alaska in late May and tracked to
Greenland by early October.3 Such wide-ranging movements allow rapid
adjustments to the Arctic’s annually varying food supplies. However it presents
great difficulties for any mark and recapture study. Deciding if a bear was
traveling or died thus becomes guesswork, and the amount of guesswork
increases with shorter studies.

Instead of erecting barriers, a small percentage of female bears
are equipped with radio collars. (Males have such big necks the collars will
slide off. Young bears outgrow their collars too quickly and could choke
themselves to death. So typically only adult females are collared.) Because
collared bears can be tracked, there is no guesswork unless the batteries die.
If a radio-collar remains in one spot for a long time, researchers locate the
collar and determine if the bear died or just lost the collar. The vastly more
accurate survival-rate data produced by collared bears is called “biological survival”. Researchers
normally use biological survival to evaluate the accuracy of “apparent
survival”. For example, if a large percentage of collared bears survived but
simply moved out of the study area, then researchers assume a similar
percentage of marked bears had also moved away. In that case, a low apparent
survival rate was an illusion due to temporary migration and the avoidance of
detection, not death.

Amstrup diligently followed
up his earlier study on the apparent survival of South Beaufort Bears using
radio-collared bears over a 12-year period. It turned out that his high-end
apparent survival estimate of 94% was still too low. If
only natural deaths were used, polar bears had a 99.6 % biological survival
rate.4 Most bears died at the hands of hunters. If death at the
hands of hunters was also considered, then biological survival was still higher
than apparent survival, but fell to 96.9%. In 2001 Amstrup concluded that the
South Beaufort Sea population was increasing
and the current hunting quotas insured a growing population.

To appreciate the magnitude of the problem in
estimating apparent survival rates, imagine a human mark-and-recapture study in
which the local supermarket is your study area. For statistical reasons, you
can only use observations inside your defined study area to determine whether
or not your neighbors are alive or dead. (Because you recognize your neighbors’
faces, there is no need to add ear tags or body paint.) How often do you see
your neighbors in that store? Although my neighbors and I shop at the same
supermarket 2 or 3 times each week, 50+ weeks
a year, I don’t see 90% of them at the supermarket more than once every 5 to 10
years. If I was doing a human mark and recapture study, and did not see my
neighbors after 5 years, my model would assume most of my neighbors had died!
For that reason mark and recapture studies must persist for several years in
order to estimate the probability of marked animals being alive but not
observed. Otherwise they will underestimate survival. Amstrup warned, “Models that predict rapid increases or decreases in
population size would not mirror reality”

Perhaps it was the growing pressure from
adversarial lawsuits, and speculation that the polar bears were endangered from
CO2 warming, but in a subsequent series of USGS publications
coauthored by Amstrup, they suddenly emphasized the illusion of apparent
survival and downplayed biological survival to suggest the polar bears were
facing extinction. The study was far too short to reliably
estimate survival. Still during the first three years of their “extinction”
study, the researchers reported apparent survival ranging from 92?99%. The
higher estimate was the same as the biological survival rates of Amstrup’s
radio-collared bears. However apparent
survival dropped dramatically for the last two years of the study. The final
years of a study always underestimate survival because newly marked are less
likely to be observed a second time relative to bears marked in the first years
of a study. Claiming “radiotelemetry captures present
methodological difficulties” they oddly excluded radio-collared data from
critical statistical tests!5 Despite knowing that
biological survival rates had never rapidly changed before, and
despite knowing more collared bears migrated outside their study area in 2004
and 2005, the
USGS report argued polar bear survival had abruptly dropped from 96?99% in
2003, down to 77% in 2004.6

In
their first USGS report, the authors demonstrated high integrity in their
analysis and were upfront about the problems of their models, writing, “the declines we
observed in model-averaged survival rates may reflect an increase in the number
of “emigrants” toward the end of the study, and not an actual decrease in
biological survival”, and they noted male bears had
exhibited unusually high transiency.5When apparent survival
rates were high, only 24% of the collared females had wandered outside the
study area.
In contrast, during last two years of the study when apparent survival
plummeted, the number of collared bears wandering outside the study area had
nearly doubled to 47% in 2005 and 36% in 2006, but they never published their
biological survival rates. They chose to dismiss the high percentage of bears migrating
out of the study area and subjectively chose to argue fewer captured bears
meant more dead bears. The authors oddly argued that using 18 years of data the
bears are eventually observed in the study area. In keeping with my
human/supermarket analogy, it was the equivalent of labeling all your neighbors
dead if you don’t see them in the market over a two year span, because over a
ten year period you always see them at least once. We need Steve McIntyre to do
a polar bear audit!

The dramatic drop in survival meant 400 bears
suddenly died but there were no carcasses. To support their unprecedented
claims, one USGS report emphasized in the abstract that subadult males showed
reduced body condition and that was evidence of nutritional stress that lowered
survival.7 However if you read the results section and did some
math, you discover that subadult males only represented 5% of all captures. The
other 95% were stable or improving. In contrast, adult females
represented about 34% of all captures, and despite being under the most stress
due to an eight-month fast while giving birth and nursing their cubs, their
body condition had improved. That good news wasn’t ever mentioned in the abstract, you
had to search the results section: “There
was no trend in mass of adult females during the study, but the mean BCI [body
condition index] of females increased over time”.7

Their
abstract also implied “a decline in cub recruitment” to support their model’s
uncharacteristic dip in survival rates. But that too was an illusion.
Recruitment compares the number of cubs in the spring with the number of cubs
in the fall. Using older studies their observed results found that the number
of cubs per female had increased between 1982 and 2006 during the spring. This
would be expected. When the female body condition increases, they usually
produce more cubs.8 To counteract that good news, the authors then
argued there was a decline in cubs during the fall, and thus a decline in
recruitment. However they had not
surveyed in the fall since 2001.7 They were using deceptive
zombie data to support a bad model.

That is how global warming
advocates counted bears to refute the claims of the Inuit. That was the driving
evidence that led to the uplisting of the polar bear as threatened species.
Based on such studies Dr. Derocher, chairman of the IUCN’s Polar Bear
Specialist Group (PBSG) warned, “It's clear from the research that's been done
by myself and colleagues around the world that we're projecting that, by the
middle of this century, two-thirds of the polar bears will be gone from their
current populations”.

Critical Thinking Questions from the Essay

1. If the Inuits do not publish in a journal, are their estimates of polar bear populations less reliable than a published mark and recapture study?

2. If radio-collared bears are critical to analyzing survival rates and population trends, why didn't the USGS publish the survival rates of collared bears?

3. Why would the same polar bear expert publish "Models that predict rapid
increases or decreases in population size would not mirror reality", and then contradict himself and claim the bears were suddenly facing extinction?